InfoQ AI, ML and Data Engineering Trends Report 2022

Welcome to the InfoQ podcast Annual Trends Report in AI, ML and data engineering topics. I am joined today by the InfoQ editorial team, and also an external panelist. There have been a lot of innovations and developments happening in AI and ML space. Before we jump into the main part of this podcast, let's start with the introductions of our panelists. Rags, can you please introduce yourself? Rags Srinivas: Glad to be here. I was here for the previous podcast last year as well. So, things have changed quite a bit, but I focus really mainly on the big data infrastructure and the confluence of that. So quite a few developments happening there that I'd love to talk about when we get there. Myself, I work for DataStax as a developer advocate, and essentially, again, it's all about data, AI, infrastructure and how to manage your costs and how to do it efficiently. And hopefully, we'll cover all that. I'm Roland, I'm a machine learning engineer, and I hope to talk a lot about transformer models and large-scale foundational models. For InfoQ, I like to write about some of the latest innovations in deep learning, and definitely want to talk about NLP and some of the multi-modal text and image models. Srini Penchikala: Next is Daniel Dominguez. Thank you for the invitation. I like to write about the metaverse, new technologies, deep learning.